US 12,088,540 B2
Enabling smart communication networks using asset information in a supply chain environment
Alexis Cohen, Atlanta, GA (US); Jacob Mapel, Atlanta, GA (US); Hunter Shinn, Atlanta, GA (US); Zach Ritter, Atlanta, GA (US); David Lee, Atlanta, GA (US); Amanda Marotti, Atlanta, GA (US); and Barbara Hernandez, Atlanta, GA (US)
Assigned to Cox Communications, Inc., Atlanta, GA (US)
Filed by Cox Communications, Inc., Atlanta, GA (US)
Filed on Jun. 29, 2022, as Appl. No. 17/809,863.
Prior Publication US 2024/0007423 A1, Jan. 4, 2024
Int. Cl. H04L 51/04 (2022.01); G06F 11/34 (2006.01); G06N 20/00 (2019.01); H04L 67/306 (2022.01)
CPC H04L 51/04 (2013.01) [G06F 11/3438 (2013.01); G06N 20/00 (2019.01); H04L 67/306 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
obtaining sensor data collected from a tracking device associated with an asset;
determining, based at least in part on the sensor data, that an adverse event occurred in connection with the asset;
providing an indication of the adverse event to a communications system;
submitting, by the communications system, a request to an intelligence engine to determine target users for the adverse event;
identifying, by a machine-learning (ML) model of the intelligence engine and based at least in part on the sensor data, a user of the communications system, wherein the ML model is used to determine that the adverse event is relevant to the user;
establishing, by the communications system, a smart communications group associated with the asset, wherein the smart communications group comprises two or more users comprising the user;
determining, by the communications system, user interactions between the two or more users of the smart communications group;
obtaining additional sensor data collected from the tracking device associated with the asset;
determining, based at least in part on the additional sensor data, resolution of the adverse event; and
updating the ML model based at least in part on the user interactions.